Unique id generation for sensors

ABSTRACT

Systems, methods, and computer-readable media are provided for generating a unique ID for a sensor in a network. Once the sensor is installed on a component of the network, the sensor can send attributes of the sensor to a control server of the network. The attributes of the sensor can include at least one unique identifier of the sensor or the host component of the sensor. The control server can determine a hash value using a one-way hash function and a secret key, send the hash value to the sensor, and designate the hash value as a sensor ID of the sensor. In response to receiving the sensor ID, the sensor can incorporate the sensor ID in subsequent communication messages. Other components of the network can verify the validity of the sensor using a hash of the at least one unique identifier of the sensor and the secret key.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a Continuation of, and claims priority to, U.S.Non-Provisional patent application Ser. No. 15/163,605, entitled “UNIQUEID GENERATION FOR SENSORS,” filed May 24, 2016, which claims the benefitof U.S. Provisional Application No. 62/171,899, entitled “SYSTEM FORMONITORING AND MANAGING DATACENTERS,” filed Jun. 5, 2015, the contentsof which are incorporated herein by reference in their entireties.

TECHNICAL FIELD

The present technology pertains to network analytics, and morespecifically to sensors in a network environment.

BACKGROUND

A modern computer network may comprise a large number of sensors. It ispossible that there are one or more identification (ID) collisionsbetween assigned IDs of these sensors. It may be an issue for sensorsassigned with conflicted IDs to effectively communicate with othersensors or nodes in the network.

Thus, there is a need to generate and assign unique sensor IDs in anetwork.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to describe the manner in which the above-recited and otheradvantages and features of the disclosure can be obtained, a moreparticular description of the principles briefly described above will berendered by reference to specific examples thereof, which areillustrated in the appended drawings. Understanding that these drawingsdepict only exemplary examples of the disclosure and are not thereforeto be considered to be limiting of its scope, the principles herein aredescribed and explained with additional specificity and detail throughthe use of the accompanying drawings in which:

FIG. 1 illustrates a diagram of an example network environment,according to some examples;

FIG. 2A illustrates a schematic diagram of an example sensor deploymentin a virtualized environment, according to some examples;

FIG. 2B illustrates a schematic diagram of an example sensor deploymentin an example network device, according to some examples;

FIG. 2C illustrates a schematic diagram of an example reporting systemin an example sensor topology, according to some examples;

FIG. 3 illustrates a sequence diagram of an example communicationbetween a sensor and a control server, according to some examples;

FIG. 4 illustrates an example method for generating a unique ID for asensor in a network, according to some examples;

FIG. 5 illustrates another example method for generating a unique ID fora sensor in a network, according to some examples;

FIG. 6 illustrates an example network device, according to someexamples; and

FIGS. 7A and 7B illustrate example system examples.

DESCRIPTION OF EXAMPLES

Various examples of the disclosure are discussed in detail below. Whilespecific implementations are discussed, it should be understood thatthis is done for illustration purposes only. A person skilled in therelevant art will recognize that other components and configurations maybe used without parting from the spirit and scope of the disclosure.

Overview

Additional features and advantages of the disclosure will be set forthin the description which follows. The features and advantages of thedisclosure can be realized and obtained by means of the instruments andcombinations particularly pointed out in the appended claims. These andother features of the disclosure will become more fully apparent fromthe following description and appended claims, or can be learned by thepractice of the principles set forth herein.

The approaches set forth herein can be used to deploy sensors in anetwork environment, assign unique identifications (IDs) for thesensors, and analyze data collected from the sensors to monitor andtroubleshoot the network. For examples, sensors can be placed at variousdevices or components in the network to collect flow data and networkstatistics from various network nodes. Once a sensor is installed on acomponent (e.g., a virtual machine (VM)) of the network, the sensor cansend attributes of the sensor to a control server of the network. Theattributes of the sensor can include at least one unique identifier ofthe sensor or the host component of the sensor. The control server candetermine a hash value using a one-way hash function and a secret key,send the hash value to the sensor, and designate the hash value as asensor ID of the sensor. In response to receiving the sensor ID, thesensor can incorporate the sensor ID in subsequent communicationmessages. Other components of the network can verify the validity of thesensor using a hash of the at least one unique identifier of the sensorand the secret key.

The at least one unique identifier of the sensor or the host componentof the sensor may include, but is not limited to, host name, mediaaccess control (MAC) address, and BIOS_UUID etc. The BIOS_UUID is auniversally unique identifier (UUID) of a part of the basic input/outputsystem (BIOS) of the host component.

Some examples can migrate a sensor across a network together with a hostcomponent of the sensor. For example, the sensor may be migratedtogether with a VM host. Since the VM host is not changed, host name,the MAC address, and/or BIOS_UUID associated with the sensor remainunchanged. The control server may determine the same hash value as thesensor ID for the sensor.

In some examples, a host component hosting a sensor can be cloned tohost the sensor. Since the cloned host component has a different hostname, MAC address, and/or BIOS_UUID, the sensor reports a differentunique identifier to a controller server. The control server candetermine a new hash value using the one-way hash function and thesecret key, and then assign the new hash value as a new sensor ID forthe sensor.

In some examples, a hash value is a fixed-length hash value using aone-way hash function and various lengths of an input that compriseshost name, MAC address, and/or BIOS_UUID. Even a slight change in aninput string may cause the hash value to change drastically. Forexample, if 1 bit of the input string is flipped, at least half of thebits in the hash value may be flipped as a result. It's difficult foreither context or length of the input to be recovered. The one-way hashfunction may include, but is not limited to, hashed messageauthentication code (HMAC), message digest 2 (MD2), MD4, MD5, securehash algorithm-1 (SHA-1), SHA-2, and SHA-3. A length of the fixed-lengthhash value can be at least 64-bit. For example, a length of thefixed-length hash value can be 128-bit using MD2 or 160-bit using SHA-1.

In some examples, a hash value determined has an arbitrary output lengthusing a one-way hash function and various lengths of an input thatcomprises host name, MAC address, and/or BIOS_UUID. The one-way hashfunction may include, but is not limited to, a family of spongefunctions such as KECCAK.

DETAILED DESCRIPTION

The disclosed technology addresses the need in the art for generatingunique sensor IDs in a network. Disclosed are systems, methods, andcomputer-readable storage media for generating a unique sensor ID for asensor in a network based on information collected from the sensor. Adescription of an example network environment, as illustrated in FIG. 1,is first disclosed herein. A discussion of sensors and sensor topologiesin virtualized environments, as illustrated in FIGS. 2A-C, will thenfollow. The discussion follows with a discussion of mechanisms forgenerating a unique sensor ID, as illustrated in FIG. 3. Then, examplemethods practiced according to the various examples disclosed hereinwill be discussed, as illustrated in FIGS. 4-5. The discussion thenconcludes with a description of example devices, as illustrated in FIGS.6 and 7A-B. These variations shall be described herein as the variousexamples are set forth. The disclosure now turns to FIG. 1.

FIG. 1 illustrates a diagram of example network environment 100. Fabric112 can represent the underlay (i.e., physical network) of networkenvironment 100. Fabric 112 can include spine routers 1-N (102 _(A-N))(collectively “102”) and leaf routers 1-N (104 _(A-N)) (collectively“104”). Leaf routers 104 can reside at the edge of fabric 112, and canthus represent the physical network edges. Leaf routers 104 can be, forexample, top-of-rack (“ToR”) switches, aggregation switches, gateways,ingress and/or egress switches, provider edge devices, and/or any othertype of routing or switching device.

Leaf routers 104 can be responsible for routing and/or bridging tenantor endpoint packets and applying network policies. Spine routers 102 canperform switching and routing within fabric 112. Thus, networkconnectivity in fabric 112 can flow from spine routers 102 to leafrouters 104, and vice versa.

Leaf routers 104 can provide servers 1-5 (106 _(A-E)) (collectively“106”), hypervisors 1-4 (108 _(A)-108 _(D)) (collectively “108”), andvirtual machines (VMs) 1-5 (110 _(A)-110 _(E)) (collectively “110”)access to fabric 112. For example, leaf routers 104 can encapsulate anddecapsulate packets to and from servers 106 in order to enablecommunications throughout environment 100. Leaf routers 104 can alsoconnect other devices, such as device 114, with fabric 112. Device 114can be any network-capable device(s) or network(s), such as a firewall,a database, a server, a collector 118 (further described below), anengine 120 (further described below), etc. Leaf routers 104 can alsoprovide any other servers, resources, endpoints, external networks, VMs,services, tenants, or workloads with access to fabric 112.

VMs 110 can be virtual machines hosted by hypervisors 108 running onservers 106. VMs 110 can include workloads running on a guest operatingsystem on a respective server. Hypervisors 108 can provide a layer ofsoftware, firmware, and/or hardware that creates and runs the VMs 110.Hypervisors 108 can allow VMs 110 to share hardware resources on servers106, and the hardware resources on servers 106 to appear as multiple,separate hardware platforms. Moreover, hypervisors 108 and servers 106can host one or more VMs 110. For example, server 106 _(A) andhypervisor 108 _(A) can host VMs 110 _(A-B).

In some cases, VMs 110 and/or hypervisors 108 can be migrated to otherservers 106. For example, VM 110 _(A) can be migrated to server 106 cand hypervisor 108 _(B). Servers 106 can similarly be migrated to otherlocations in network environment 100. For example, a server connected toa specific leaf router can be changed to connect to a different oradditional leaf router. In some cases, some or all of servers 106,hypervisors 108, and/or VMs 110 can represent tenant space. Tenant spacecan include workloads, services, applications, devices, and/or resourcesthat are associated with one or more clients or subscribers.Accordingly, traffic in network environment 100 can be routed based onspecific tenant policies, spaces, agreements, configurations, etc.Moreover, addressing can vary between one or more tenants. In someconfigurations, tenant spaces can be divided into logical segmentsand/or networks and separated from logical segments and/or networksassociated with other tenants.

Any of leaf routers 104, servers 106, hypervisors 108, and VMs 110 caninclude sensor 116 (also referred to as a “sensor”) configured tocapture network data, and report any portion of the captured data tocollector 118. Sensors 116 can be processes, agents, modules, drivers,or components deployed on a respective system (e.g., a server, VM,hypervisor, leaf router, etc.), configured to capture network data forthe respective system (e.g., data received or transmitted by therespective system), and report some or all of the captured data tocollector 118.

For example, a VM sensor can run as a process, kernel module, or kerneldriver on the guest operating system installed in a VM and configured tocapture data (e.g., network and/or system data) processed (e.g., sent,received, generated, etc.) by the VM. Additionally, a hypervisor sensorcan run as a process, kernel module, or kernel driver on the hostoperating system installed at the hypervisor layer and configured tocapture data (e.g., network and/or system data) processed (e.g., sent,received, generated, etc.) by the hypervisor. A server sensor can run asa process, kernel module, or kernel driver on the host operating systemof a server and configured to capture data (e.g., network and/or systemdata) processed (e.g., sent, received, generated, etc.) by the server.And a network device sensor can run as a process or component in anetwork device, such as leaf routers 104, and configured to capture data(e.g., network and/or system data) processed (e.g., sent, received,generated, etc.) by the network device.

Sensors 116 can be configured to report the observed data and/ormetadata about one or more packets, flows, communications, processes,events, and/or activities to collector 118. For example, sensors 116 cancapture network data as well as information about the system or host ofthe sensors 116 (e.g., where the sensors 116 are deployed). Suchinformation can also include, for example, data or metadata of active orpreviously active processes of the system, operating system useridentifiers, metadata of files on the system, system alerts, networkinginformation, etc. Sensors 116 may also analyze all the processes runningon the respective VMs, hypervisors, servers, or network devices todetermine specifically which process is responsible for a particularflow of network traffic. Similarly, sensors 116 may determine whichoperating system user(s) is responsible for a given flow. Reported datafrom sensors 116 can provide details or statistics particular to one ormore tenants. For example, reported data from a subset of sensors 116deployed throughout devices or elements in a tenant space can provideinformation about the performance, use, quality, events, processes,security status, characteristics, statistics, patterns, conditions,configurations, topology, and/or any other information for theparticular tenant space.

Collectors 118 can be one or more devices, modules, workloads and/orprocesses capable of receiving data from sensors 116. Collectors 118 canthus collect reports and data from sensors 116. Collectors 118 can bedeployed anywhere in network environment 100 and/or even on remotenetworks capable of communicating with network environment 100. Forexample, one or more collectors can be deployed within fabric 112 or onone or more of the servers 106. One or more collectors can be deployedoutside of fabric 112 but connected to one or more leaf routers 104.Collectors 118 can be part of servers 106 and/or separate servers ordevices (e.g., device 114). Collectors 118 can also be implemented in acluster of servers.

Collectors 118 can be configured to collect data from sensors 116. Inaddition, collectors 118 can be implemented in one or more servers in adistributed fashion. As previously noted, collectors 118 can include oneor more collectors. Moreover, each collector can be configured toreceive reported data from all sensors 116 or a subset of sensors 116.For example, a collector can be assigned to a subset of sensors 116 sothe data received by that specific collector is limited to data from thesubset of sensors.

Collectors 118 can be configured to aggregate data from all sensors 116and/or a subset of sensors 116. Moreover, collectors 118 can beconfigured to analyze some or all of the data reported by sensors 116.For example, collectors 118 can include analytics engines (e.g., engines120) for analyzing collected data. Environment 100 can also includeseparate analytics engines 120 configured to analyze the data reportedto collectors 118. For example, engines 120 can be configured to receivecollected data from collectors 118 and aggregate the data, analyze thedata (individually and/or aggregated), generate reports, identifyconditions, compute statistics, visualize reported data, troubleshootconditions, visualize the network and/or portions of the network (e.g.,a tenant space), generate alerts, identify patterns, calculatemisconfigurations, identify errors, generate suggestions, generatetesting, and/or perform any other analytics functions.

While collectors 118 and engines 120 are shown as separate entities,this is for illustration purposes as other configurations are alsocontemplated herein. For example, any of collectors 118 and engines 120can be part of a same or separate entity. Moreover, any of thecollector, aggregation, and analytics functions can be implemented byone entity (e.g., collectors 118) or separately implemented by multipleentities (e.g., engine 120 and/or collectors 118).

Each of the sensors 116 can use a respective address (e.g., internetprotocol (IP) address, port number, etc.) of their host to sendinformation to collectors 118 and/or any other destination. Collectors118 may also be associated with their respective addresses such as IPaddresses. Moreover, sensors 116 can periodically send information aboutflows they observe to collectors 118. Sensors 116 can be configured toreport each and every flow they observe. Sensors 116 can report a listof flows that were active during a period of time (e.g., between thecurrent time and the time of the last report). The consecutive periodsof time of observance can be represented as pre-defined or adjustabletime series. The series can be adjusted to a specific level ofgranularity. Thus, the time periods can be adjusted to control the levelof details in statistics and can be customized based on specificrequirements, such as security, scalability, storage, etc. The timeseries information can also be implemented to focus on more importantflows or components (e.g., VMs) by varying the time intervals. Thecommunication channel between a sensor and collector 118 can also createa flow in every reporting interval. Thus, the information transmitted orreported by sensors 116 can also include information about the flowcreated by the communication channel.

FIG. 2A illustrates a schematic diagram of an example sensor deployment200 in a virtualized environment. Server 106 _(A) can execute and hostone or more VMs 202 _(A-C) (collectively “202”). VMs 202 _(A-C) can besimilar to VMs 110 _(A-E) of FIG. 1. For example, VM 1 (202 _(A)) ofFIG. 2A can be VM 1 (110 _(A)) of FIG. 1, and so forth. VMs 202 can beconfigured to run workloads (e.g., applications, services, processes,functions, etc.) based on hardware resources 212 on server 106 _(A). VMs202 can run on guest operating systems 206 _(A-C) (collectively “206”)on a virtual operating platform provided by hypervisor 208. Each VM 202can run a respective guest operating system 206 which can be the same ordifferent as other guest operating systems 206 associated with other VMs202 on server 106 _(A). Each of guest operating systems 206 can executeone or more processes, which may in turn be programs, applications,modules, drivers, services, widgets, etc. Each of guest operatingsystems 206 may also be associated with one or more user accounts. Forexample, many popular operating systems such as LINUX, UNIX, WINDOWS,MAC OS, etc., offer multi-user environments where one or more users canuse the system concurrently and share software/hardware resources. Oneor more users can sign in or log in to their user accounts associatedwith the operating system and run various workloads. Moreover, each VM202 can have one or more network addresses, such as an internet protocol(IP) address. VMs 202 can thus communicate with hypervisor 208, server106 _(A), and/or any remote devices or networks using the one or morenetwork addresses.

Hypervisor 208 (otherwise known as a virtual machine monitor) can be alayer of software, firmware, and/or hardware that creates and runs VMs202. Guest operating systems 206 running on VMs 202 can sharevirtualized hardware resources created by hypervisor 208. Thevirtualized hardware resources can provide the illusion of separatehardware components. Moreover, the virtualized hardware resources canperform as physical hardware components (e.g., memory, storage,processor, network interface, etc.), and can be driven by hardwareresources 212 on server 106 _(A). Hypervisor 208 can have one or morenetwork addresses, such as an internet protocol (IP) address, tocommunicate with other devices, components, or networks. For example,hypervisor 208 can have a dedicated IP address which it can use tocommunicate with VMs 202, server 106 _(A), and/or any remote devices ornetworks.

Hardware resources 212 of server 106 _(A) can provide the underlyingphysical hardware that drives operations and functionalities provided byserver 106 _(A), hypervisor 208, and VMs 202. Hardware resources 212 caninclude, for example, one or more memory resources, one or more storageresources, one or more communication interfaces, one or more processors,one or more circuit boards, one or more buses, one or more extensioncards, one or more power supplies, one or more antennas, one or moreperipheral components, etc. Additional examples of hardware resourcesare described below with reference to FIGS. 6 and 7A-B.

Server 106 _(A) can also include one or more host operating systems (notshown). The number of host operating system can vary by configuration.For example, some configurations can include a dual boot configurationthat allows server 106 _(A) to boot into one of multiple host operatingsystems. In other configurations, server 106 _(A) may run a single hostoperating system. Host operating systems can run on hardware resources212. In some cases, hypervisor 208 can run on, or utilize, a hostoperating system on server 106 _(A). Each of the host operating systemscan execute one or more processes, which may be programs, applications,modules, drivers, services, widgets, etc. Each of the host operatingsystems may also be associated with one or more OS user accounts.

Server 106 _(A) can also have one or more network addresses, such as aninternet protocol (IP) address, to communicate with other devices,components, or networks. For example, server 106 _(A) can have an IPaddress assigned to a communications interface from hardware resources212, which it can use to communicate with VMs 202, hypervisor 208, leafrouter 104 _(A) in FIG. 1, collectors 118 in FIG. 1, and/or any remotedevices or networks.

VM sensors 204 _(A-C) (collectively “204”) can be deployed on one ormore of VMs 202. VM sensors 204 can be data and packet inspection agentsor sensors deployed on VMs 202 to capture packets, flows, processes,events, traffic, and/or any data flowing into, out of, or through VMs202. VM sensors 204 can be configured to export or report any datacollected or captured by the sensors 204 to a remote entity, such ascollectors 118, for example. VM sensors 204 can communicate or reportsuch data using a network address of the respective VMs 202 (e.g., VM IPaddress).

VM sensors 204 can capture and report any traffic (e.g., packets, flows,etc.) sent, received, generated, and/or processed by VMs 202. Forexample, sensors 204 can report every packet or flow of communicationsent and received by VMs 202. Such communication channel between sensors204 and collectors 108 creates a flow in every monitoring period orinterval and the flow generated by sensors 204 may be denoted as acontrol flow. Moreover, any communication sent or received by VMs 202,including data reported from sensors 204, can create a network flow. VMsensors 204 can report such flows in the form of a control flow to aremote device, such as collectors 118 illustrated in FIG. 1. VM sensors204 can report each flow separately or aggregated with other flows. Whenreporting a flow via a control flow, VM sensors 204 can include a sensoridentifier that identifies sensors 204 as reporting the associated flow.VM sensors 204 can also include in the control flow a flow identifier,an IP address, a timestamp, metadata, a process ID, an OS usernameassociated with the process ID, and any other information, as furtherdescribed below. In addition, sensors 204 can append the process anduser information (i.e., which process and/or user is associated with aparticular flow) to the control flow. The additional information asidentified above can be applied to the control flow as labels.Alternatively, the additional information can be included as part of aheader, a trailer, or a payload.

VM sensors 204 can also report multiple flows as a set of flows. Whenreporting a set of flows, VM sensors 204 can include a flow identifierfor the set of flows and/or a flow identifier for each flow in the setof flows. VM sensors 204 can also include one or more timestamps andother information as previously explained.

VM sensors 204 can run as a process, kernel module, or kernel driver onguest operating systems 206 of VMs 202. VM sensors 204 can thus monitorany traffic sent, received, or processed by VMs 202, any processesrunning on guest operating systems 206, any users and user activities onguest operating system 206, any workloads on VMs 202, etc.

Hypervisor sensor 210 can be deployed on hypervisor 208. Hypervisorsensor 210 can be a data inspection agent or a sensor deployed onhypervisor 208 to capture traffic (e.g., packets, flows, etc.) and/ordata flowing through hypervisor 208. Hypervisor sensor 210 can beconfigured to export or report any data collected or captured byhypervisor sensor 210 to a remote entity, such as collectors 118, forexample. Hypervisor sensor 210 can communicate or report such data usinga network address of hypervisor 208, such as an IP address of hypervisor208.

Because hypervisor 208 can see traffic and data originating from VMs202, hypervisor sensor 210 can also capture and report any data (e.g.,traffic data) associated with VMs 202. For example, hypervisor sensor210 can report every packet or flow of communication sent or received byVMs 202 and/or VM sensors 204. Moreover, any communication sent orreceived by hypervisor 208, including data reported from hypervisorsensor 210, can create a network flow. Hypervisor sensor 210 can reportsuch flows in the form of a control flow to a remote device, such ascollectors 118 illustrated in FIG. 1. Hypervisor sensor 210 can reporteach flow separately and/or in combination with other flows or data.When reporting a flow, hypervisor sensor 210 can include a sensoridentifier that identifies hypervisor sensor 210 as reporting the flow.Hypervisor sensor 210 can also include in the control flow a flowidentifier, an IP address, a timestamp, metadata, a process ID, and anyother information, as explained below. In addition, sensors 210 canappend the process and user information (i.e., which process and/or useris associated with a particular flow) to the control flow. Theadditional information as identified above can be applied to the controlflow as labels. Alternatively, the additional information can beincluded as part of a header, a trailer, or a payload.

Hypervisor sensor 210 can also report multiple flows as a set of flows.When reporting a set of flows, hypervisor sensor 210 can include a flowidentifier for the set of flows and/or a flow identifier for each flowin the set of flows. Hypervisor sensor 210 can also include one or moretimestamps and other information as previously explained, such asprocess and user information.

As previously explained, any communication captured or reported by VMsensors 204 can flow through hypervisor 208. Thus, hypervisor sensor 210can observe and capture any flows or packets reported by VM sensors 204,including any control flows. Accordingly, hypervisor sensor 210 can alsoreport any packets or flows reported by VM sensors 204 and any controlflows generated by VM sensors 204. For example, VM sensor 204 _(A) on VM1 (202 _(A)) captures flow 1 (“F 1”) and reports F1 to collector 118 onFIG. 1. Hypervisor sensor 210 on hypervisor 208 can also see and captureF1, as F1 would traverse hypervisor 208 when being sent or received byVM 1 (202 _(A)). Accordingly, hypervisor sensor 210 on hypervisor 208can also report F1 to collector 118. Thus, collector 118 can receive areport of F1 from VM sensor 204 _(A) on VM 1 (202 _(A)) and anotherreport of F1 from hypervisor sensor 210 on hypervisor 208.

When reporting F1, hypervisor sensor 210 can report F1 as a message orreport that is separate from the message or report of F1 transmitted byVM sensor 204 _(A) on VM 1 (202 _(A)). However, hypervisor sensor 210can also, or otherwise, report F1 as a message or report that includesor appends the message or report of F1 transmitted by VM sensor 204 _(A)on VM 1 (202 _(A)). In other words, hypervisor sensor 210 can report F1as a separate message or report from VM sensor 204 _(A)'s message orreport of F1, and/or a same message or report that includes both areport of F1 by hypervisor sensor 210 and the report of F1 by VM sensor204 _(A) at VM 1 (202 _(A)). In this way, VM sensors 204 at VMs 202 canreport packets or flows received or sent by VMs 202, and hypervisorsensor 210 at hypervisor 208 can report packets or flows received orsent by hypervisor 208, including any flows or packets received or sentby VMs 202 and/or reported by VM sensors 204.

Hypervisor sensor 210 can run as a process, kernel module, or kerneldriver on the host operating system associated with hypervisor 208.Hypervisor sensor 210 can thus monitor any traffic sent and received byhypervisor 208, any processes associated with hypervisor 208, etc.

Server 106 _(A) can also have server sensor 214 running on it. Serversensor 214 can be a data inspection agent or sensor deployed on server106 _(A) to capture data (e.g., packets, flows, traffic data, etc.) onserver 106 _(A). Server sensor 214 can be configured to export or reportany data collected or captured by server sensor 214 to a remote entity,such as collector 118, for example. Server sensor 214 can communicate orreport such data using a network address of server 106 _(A), such as anIP address of server 106 _(A).

Server sensor 214 can capture and report any packet or flow ofcommunication associated with server 106 _(A). For example, sensor 216can report every packet or flow of communication sent or received by oneor more communication interfaces of server 106 _(A). Moreover, anycommunication sent or received by server 106 _(A), including datareported from sensors 204 and 210, can create a network flow associatedwith server 106 _(A). Server sensor 214 can report such flows in theform of a control flow to a remote device, such as collector 118illustrated in FIG. 1. Server sensor 214 can report each flow separatelyor in combination. When reporting a flow, server sensor 214 can includea sensor identifier that identifies server sensor 214 as reporting theassociated flow. Server sensor 214 can also include in the control flowa flow identifier, an IP address, a timestamp, metadata, a process ID,and any other information. In addition, sensor 214 can append theprocess and user information (i.e., which process and/or user isassociated with a particular flow) to the control flow. The additionalinformation as identified above can be applied to the control flow aslabels. Alternatively, the additional information can be included aspart of a header, a trailer, or a payload.

Server sensor 214 can also report multiple flows as a set of flows. Whenreporting a set of flows, server sensor 214 can include a flowidentifier for the set of flows and/or a flow identifier for each flowin the set of flows. Server sensor 214 can also include one or moretimestamps and other information as previously explained.

Any communications captured or reported by sensors 204 and 210 can flowthrough server 106 _(A). Thus, server sensor 214 can observe or captureany flows or packets reported by sensors 204 and 210. In other words,network data observed by sensors 204 and 210 inside VMs 202 andhypervisor 208 can be a subset of the data observed by server sensor 214on server 106 _(A). Accordingly, server sensor 214 can report anypackets or flows reported by sensors 204 and 210 and any control flowsgenerated by sensors 204 and 210. For example, sensor 204 _(A) on VM 1(202 _(A)) captures flow 1 (F1) and reports F1 to collector 118 asillustrated on FIG. 1. sensor 210 on hypervisor 208 can also observe andcapture F1, as F1 would traverse hypervisor 208 when being sent orreceived by VM 1 (202 _(A)). In addition, sensor 214 on server 106 _(A)can also see and capture F1, as F1 would traverse server 106 _(A) whenbeing sent or received by VM 1 (202 _(A)) and hypervisor 208.Accordingly, sensor 214 can also report F1 to collector 118. Thus,collector 118 can receive a report (i.e., control flow) regarding F1from sensor 204 _(A) on VM 1 (202 _(A)), sensor 210 on hypervisor 208,and sensor 214 on server 106 _(A).

When reporting F1, server sensor 214 can report F1 as a message orreport that is separate from any messages or reports of F1 transmittedby sensor 204 _(A) on VM 1 (202 _(A)) or sensor 210 on hypervisor 208.However, server sensor 214 can also, or otherwise, report F1 as amessage or report that includes or appends the messages or reports ormetadata of F1 transmitted by sensor 204 _(A) on VM 1 (202 _(A)) andsensor 210 on hypervisor 208. In other words, server sensor 214 canreport F1 as a separate message or report from the messages or reportsof F1 from sensor 204 _(A) and sensor 210, and/or a same message orreport that includes a report of F1 by sensor 204 _(A), sensor 210, andsensor 214. In this way, sensors 204 at VMs 202 can report packets orflows received or sent by VMs 202, sensor 210 at hypervisor 208 canreport packets or flows received or sent by hypervisor 208, includingany flows or packets received or sent by VMs 202 and reported by sensors204, and sensor 214 at server 106 _(A) can report packets or flowsreceived or sent by server 106 _(A), including any flows or packetsreceived or sent by VMs 202 and reported by sensors 204, and any flowsor packets received or sent by hypervisor 208 and reported by sensor210.

Server sensor 214 can run as a process, kernel module, or kernel driveron the host operating system or a hardware component of server 106 _(A).Server sensor 214 can thus monitor any traffic sent and received byserver 106 _(A), any processes associated with server 106 _(A), etc.

In addition to network data, sensors 204, 210, and 214 can captureadditional information about the system or environment in which theyreside. For example, sensors 204, 210, and 214 can capture data ormetadata of active or previously active processes of their respectivesystem or environment, operating system user identifiers, metadata offiles on their respective system or environment, timestamps, networkaddressing information, flow identifiers, sensor identifiers, etc.Moreover, sensors 204, 210, 214 are not specific to any operating systemenvironment, hypervisor environment, network environment, or hardwareenvironment. Thus, sensors 204, 210, and 214 can operate in anyenvironment.

As previously explained, sensors 204, 210, and 214 can send informationabout the network traffic they observe. This information can be sent toone or more remote devices, such as one or more servers, collectors,engines, etc. Each sensor can be configured to send respectiveinformation using a network address, such as an IP address, and anyother communication details, such as port number, to one or moredestination addresses or locations. Sensors 204, 210, and 214 can sendmetadata about one or more flows, packets, communications, processes,events, etc.

Sensors 204, 210, and 214 can periodically report information about eachflow or packet they observe. The information reported can contain a listof flows or packets that were active during a period of time (e.g.,between the current time and the time at which the last information wasreported). The communication channel between the sensor and thedestination can create a flow in every interval. For example, thecommunication channel between sensor 214 and collector 118 can create acontrol flow. Thus, the information reported by a sensor can alsocontain information about this control flow. For example, theinformation reported by sensor 214 to collector 118 can include a listof flows or packets that were active at hypervisor 208 during a periodof time, as well as information about the communication channel betweensensor 210 and collector 118 used to report the information by sensor210.

FIG. 2B illustrates a schematic diagram of example sensor deployment 220in an example network device. The network device is described as leafrouter 104 _(A), as illustrated in FIG. 1. However, this is forexplanation purposes. The network device can be any other networkdevice, such as any other switch, router, etc.

In this example, leaf router 104 _(A) can include network resources 222,such as memory, storage, communication, processing, input, output, andother types of resources. Leaf router 104 _(A) can also includeoperating system environment 224. The operating system environment 224can include any operating system, such as a network operating system,embedded operating system, etc. Operating system environment 224 caninclude processes, functions, and applications for performingnetworking, routing, switching, forwarding, policy implementation,messaging, monitoring, and other types of operations.

Leaf router 104 _(A) can also include sensor 226. Sensor 226 can be anagent or sensor configured to capture network data, such as flows orpackets, sent received, or processed by leaf router 104 _(A). Sensor 226can also be configured to capture other information, such as processes,statistics, users, alerts, status information, device information, etc.Moreover, sensor 226 can be configured to report captured data to aremote device or network, such as collector 118 shown in FIG. 1, forexample. Sensor 226 can report information using one or more networkaddresses associated with leaf router 104 _(A) or collector 118. Forexample, sensor 226 can be configured to report information using an IPassigned to an active communications interface on leaf router 104 _(A).

Leaf router 104 _(A) can be configured to route traffic to and fromother devices or networks, such as server 106 _(A). Accordingly, sensor226 can also report data reported by other sensors on other devices. Forexample, leaf router 104 _(A) can be configured to route traffic sentand received by server 106 _(A) to other devices. Thus, data reportedfrom sensors deployed on server 106 _(A), such as VM and hypervisorsensors on server 106 _(A), would also be observed by sensor 226 and canthus be reported by sensor 226 as data observed at leaf router 104 _(A).Such report can be a control flow generated by sensor 226. Data reportedby the VM and hypervisor sensors on server 106 _(A) can therefore be asubset of the data reported by sensor 226.

Sensor 226 can run as a process or component (e.g., firmware, module,hardware device, etc.) in leaf router 104 _(A). Moreover, sensor 226 canbe installed on leaf router 104 _(A) as a software or firmware agent. Insome configurations, leaf router 104 _(A) itself can act as sensor 226.Moreover, sensor 226 can run within operating system 224 and/or separatefrom operating system 224.

FIG. 2C illustrates a schematic diagram of example reporting system 240in an example sensor topology. Leaf router 104 _(A) can route packets ortraffic 242 between fabric 112 and server 106 _(A), hypervisor 108 _(A),and VM 110 _(A). Packets or traffic 242 between VM 110 _(A) and leafrouter 104 _(A) can flow through hypervisor 108 _(A) and server 106_(A). Packets or traffic 242 between hypervisor 108 _(A) and leaf router104 _(A) can flow through server 106 _(A). Finally, packets or traffic242 between server 106 _(A) and leaf router 104 _(A) can flow directlyto leaf router 104 _(A). However, in some cases, packets or traffic 242between server 106 _(A) and leaf router 104 _(A) can flow through one ormore intervening devices or networks, such as a switch or a firewall.

Moreover, VM sensor 204 _(A) at VM 110 _(A), hypervisor sensor 210 athypervisor 108 _(A), network device sensor 226 at leaf router 104 _(A),and any server sensor at server 106 _(A) (e.g., sensor running on hostenvironment of server 106 _(A)) can send reports 244 (also referred toas control flows) to collector 118 based on the packets or traffic 242captured at each respective sensor. Reports 244 from VM sensor 204 _(A)to collector 118 can flow through VM 110 _(A), hypervisor 108 _(A),server 106 _(A), and leaf router 104 _(A). Reports 244 from hypervisorsensor 210 to collector 118 can flow through hypervisor 108 _(A), server106 _(A), and leaf router 104 _(A). Reports 244 from any other serversensor at server 106 _(A) to collector 118 can flow through server 106_(A) and leaf router 104 _(A). Finally, reports 244 from network devicesensor 226 to collector 118 can flow through leaf router 104 _(A).Although reports 244 are depicted as being routed separately fromtraffic 242 in FIG. 2C, one of ordinary skill in the art will understandthat reports 244 and traffic 242 can be transmitted through the samecommunication channel(s).

Reports 244 can include any portion of packets or traffic 242 capturedat the respective sensors. Reports 244 can also include otherinformation, such as timestamps, process information, sensoridentifiers, flow identifiers, flow statistics, notifications, logs,user information, system information, addresses, ports, protocols, etc.Some or all of this information can be appended to reports 244 as one ormore labels, metadata, or as part of the packet(s)' header, trailer, orpayload. For example, if a user opens a browser on VM 110 _(A) andnavigates to examplewebsite.com, VM sensor 204 _(A) of VM 110 _(A) candetermine which user (i.e., operating system user) of VM 110 _(A) (e.g.,username “johndoe85”) and which process being executed on the operatingsystem of VM 110 _(A) (e.g., “chrome.exe”) were responsible for theparticular network flow to and from examplewebsite.com. Once suchinformation is determined, the information can be included in report 244as labels for example, and report 244 can be transmitted from VM sensor204 _(A) to collector 118. Such additional information can help system240 to gain insight into flow information at the process and user level,for instance. This information can be used for security, optimization,and determining structures and dependencies within system 240. Moreover,reports 244 can be transmitted to collector 118 periodically as newpackets or traffic 242 are captured by a sensor. Further, each sensorcan send a single report or multiple reports to collector 118. Forexample, each of the sensors 116 can be configured to send a report tocollector 118 for every flow, packet, message, communication, or networkdata received, transmitted, and/or generated by its respective host(e.g., VM 110 _(A), hypervisor 108 _(A), server 106 _(A), and leafrouter 104 _(A)). As such, collector 118 can receive a report of a samepacket from multiple sensors.

For example, a packet received by VM 110 _(A) from fabric 112 can becaptured and reported by VM sensor 204 _(A). Since the packet receivedby VM 110 _(A) will also flow through leaf router 104 _(A) andhypervisor 108 _(A), it can also be captured and reported by hypervisorsensor 210 and network device sensor 226. Thus, for a packet received byVM 110 _(A) from fabric 112, collector 118 can receive a report of thepacket from VM sensor 204 _(A), hypervisor sensor 210, and networkdevice sensor 226.

Similarly, a packet sent by VM 110 _(A) to fabric 112 can be capturedand reported by VM sensor 204 _(A). Since the packet sent by VM 110 _(A)will also flow through leaf router 104 _(A) and hypervisor 108 _(A), itcan also be captured and reported by hypervisor sensor 210 and networkdevice sensor 226. Thus, for a packet sent by VM 110 _(A) to fabric 112,collector 118 can receive a report of the packet from VM sensor 204_(A), hypervisor sensor 210, and network device sensor 226.

On the other hand, a packet originating at, or destined to, hypervisor108 _(A), can be captured and reported by hypervisor sensor 210 andnetwork device sensor 226, but not VM sensor 204 _(A), as such packetmay not flow through VM 110 _(A). Moreover, a packet originating at, ordestined to, leaf router 104 _(A), will be captured and reported bynetwork device sensor 226, but not VM sensor 204 _(A), hypervisor sensor210, or any other sensor on server 106 _(A), as such packet may not flowthrough VM 110 _(A), hypervisor 108 _(A), or server 106 _(A).

Each of the sensors 204 _(A), 210, 226 can include a respective uniquesensor identifier on each of reports 244 it sends to collector 118, toallow collector 118 to determine which sensor sent the report. Reports244 can be used to analyze network and/or system data and conditions fortroubleshooting, security, visualization, configuration, planning, andmanagement. Sensor identifiers in reports 244 can also be used todetermine which sensors reported what flows. This information can thenbe used to determine sensor placement and topology, as further describedbelow, as well as mapping individual flows to processes and users. Suchadditional insights gained can be useful for analyzing the data inreports 244, as well as troubleshooting, security, visualization,configuration, planning, and management.

FIG. 3 illustrates a sequence diagram of an example communication 300between a sensor and a control server in a network. In this example, thecommunication 300 between a sensor 302 and a control server 304, one ormore messages such as messages 1-2 (306-308) may be exchanged betweenthe sensor 302 and the control server 304. After the sensor 302 isinstalled on a host component (e.g., a host VM), the sensor 302 can sendattributes of the sensor 302 to the control server 304 via a message 1(306). The message 1 (306) includes at least one unique identifier ofthe sensor 302 or the host component of the sensor 302.

In response to receiving the attributes of the sensor 302, the controlserver 304 can determine a hash value, using a one-way hash function anda secret key, based upon the attributes of the sensor 302. In someexamples, the hash value is a fixed length hash value that isindependent from the length of an input string to generate the hashvalue. The one-way hash function includes, HMAC, MD2, MD4, MD5, SHA-1,SHA-2, and SHA-3.

The control server 304 can then send the hash value to the sensor 302and designate the hash value as a sensor ID of the sensor. In responseto receiving the sensor ID, the sensor 302 incorporates the sensor ID inall subsequent communication messages. Other components, nodes orsensors of the network can receive communication message(s) from thesensor 302, and further verify the validity of the sensor 302. Forexample, a backend server of the network can determine a hash valuebased upon attributes of the sensor 302 using the one-way hash functionand the secret key. If the hash value is inconsistent with the sensor IDthat is incorporated in the communication message(s) of the sensor 302,the backend server can determine that the sensor 302 may be under anattack and can generate a warning report.

As one of skill in the art will appreciate, some of all of the variousmethods and rules—timing, degree, magnitude, graph consistency,historical data, hash function, etc.—as described in this disclosure canbe used in combination. Different weights can also be assigned todifferent rules and methods depending on the accuracy, margin of error,etc. of each rule or method.

Having disclosed some basic system components and concepts, thedisclosure now turns to the exemplary method examples shown in FIGS.4-5. For the sake of clarity, the methods are described in terms ofsystem 100, as shown in FIG. 1, configured to practice the method.However, the example methods can be practiced by any software orhardware components, devices, etc. heretofore disclosed, such as system200 of FIG. 2A, system 220 of FIG. 2B, system 600 of FIG. 6, system 700of FIG. 7A, system 750 of FIG. 7B, etc. The steps outlined herein areexemplary and can be implemented in any combination thereof in anyorder, including combinations that exclude, add, or modify certainsteps.

FIG. 4 illustrates an example method 400 for generating a unique ID fora sensor in a network, according to some examples. It should beunderstood that the exemplary method 400 is presented solely forillustrative purposes and that in other methods in accordance with thepresent technology can include additional, fewer, or alternative stepsperformed in similar or alternative orders, or in parallel. The system100 can receive a message from the sensor, at step 402. The messagecomprises attributes of the sensor that includes at least one uniqueidentifier of the sensor or the host component of the sensor. The hostcomponent can be an endpoint, a terminal, a server, a virtual machine, ahypervisor, a switch, a gateway, etc. The at least one unique identifierof the sensor or the host component of the sensor may include host name,MAC address, and BIOS_UUID etc.

Based on the at least one unique identifier of the sensor or the hostcomponent of the sensor, the system 100 can determine a sensor ID forthe sensor, at step 404. For example, the system 100 can determine ahash value using a one-way hash function and a secret key and designatethe hash value as the sensor ID for the sensor. The one-way hashfunction may include HMAC, MD2, MD4, MD5, SHA-1, SHA-2, SHA-3, andKECCAK.

The system 100 can then send the sensor ID to the sensor, at step 406,and cause the sensor to incorporate the sensor ID and attributes of thesensor (e.g., the at least one unique identifier of the sensor or thehost component of the sensor) in all subsequent communication messages.The system 100 or a component may receive or collect the subsequentcommunication messages from the sensor, at step 408. The system 100 canfurther determine a hash value based upon received attributes of thesensor using the one-way hash function and the secret key, and comparethe hash value with the sensor ID incorporated in the subsequentcommunication message(s), at step 410.

In response to determining that the hash value is consistent with thesensor ID, the method 400 returns to step 408 to receive or monitoradditional communication message(s) from the sensor. In response todetermining that the hash value is inconsistent with the sensor ID, thesystem 100 may generate a warning report, at step 412, to indicate thatthe system 100 or the senor may be under an attack.

FIG. 5 illustrates another example method 500 for generating a unique IDfor a sensor in a network, according to some examples. In this example,the system 100 can determine that a sensor is installed on a hostcomponent, at step 502, and then cause the sensor to send attribute ofthe sensor to a control server of the network, at step 504. Theattributes includes at least one unique identifier of the sensor or thehost component of the sensor that comprises host name, MAC address, andBIOS_UUID of the host component.

The system 100 can further cause the control server to determine asensor ID for the sensor. The sensor ID can be used to uniquely identifythe sensor in the network. The sensor ID is a hash value determinedusing a one-way hash function, a secret key, and the at least one uniqueidentifier of the sensor or the host component of the sensor.

The sensor receives the sensor ID from the control server, at step 506.The system 100 can further cause the sensor to incorporate the sensor IDand the at least one unique identifier in all subsequent communicationmessages, at step 508. The system 100 can verify the sensor based uponthe sensor ID incorporated in the subsequent communication message(s)from the sensor.

Example Devices

FIG. 6 illustrates an example network device 600 according to someexamples. Network device 600 includes a master central processing unit(CPU) 602, interfaces 604, and a bus 606 (e.g., a PCI bus). When actingunder the control of appropriate software or firmware, the CPU 602 isresponsible for executing packet management, error detection, and/orrouting functions. The CPU 602 preferably accomplishes all thesefunctions under the control of software including an operating systemand any appropriate applications software. CPU 602 may include one ormore processors 610 such as a processor from the Motorola family ofmicroprocessors or the MIPS family of microprocessors. In an alternativeexample, processor 610 is specially designed hardware for controllingthe operations of router. In a specific example, a memory 608 (such asnon-volatile RAM and/or ROM) also forms part of CPU 602. However, thereare many different ways in which memory could be coupled to the system.

The interfaces 604 are typically provided as interface cards (sometimesreferred to as “line cards”). Generally, they control the sending andreceiving of data packets over the network and sometimes support otherperipherals used with the router. Among the interfaces that may beprovided are Ethernet interfaces, frame relay interfaces, cableinterfaces, DSL interfaces, token ring interfaces, and the like. Inaddition, various very high-speed interfaces may be provided such asfast token ring interfaces, wireless interfaces, Ethernet interfaces,Gigabit Ethernet interfaces, ATM interfaces, HSSI interfaces, POSinterfaces, FDDI interfaces and the like. Generally, these interfacesmay include ports appropriate for communication with the appropriatemedia. In some cases, they may also include an independent processorand, in some instances, volatile RAM. The independent processors maycontrol such communications intensive tasks as packet switching, mediacontrol and management. By providing separate processors for thecommunications intensive tasks, these interfaces allow the mastermicroprocessor 602 to efficiently perform routing computations, networkdiagnostics, security functions, etc.

Although the system shown in FIG. 6 is one specific network device ofthe present invention, it is by no means the only network devicearchitecture on which the present invention can be implemented. Forexample, an architecture having a single processor that handlescommunications as well as routing computations, etc. is often used.Further, other types of interfaces and media could also be used with therouter.

Regardless of the network device's configuration, it may employ one ormore memories or memory modules (including memory 608) configured tostore program instructions for the general-purpose network operationsand mechanisms for roaming, route optimization and routing functionsdescribed herein. The program instructions may control the operation ofan operating system and/or one or more applications, for example. Thememory or memories may also be configured to store tables such asmobility binding, registration, and association tables, etc.

FIG. 7A and FIG. 7B illustrate example system examples. The moreappropriate example will be apparent to those of ordinary skill in theart when practicing the present technology. Persons of ordinary skill inthe art will also readily appreciate that other system examples arepossible.

FIG. 7A illustrates a conventional system bus computing systemarchitecture 700 wherein the components of the system are in electricalcommunication with each other using a bus 712. Exemplary system 700includes a processing unit (CPU or processor) 702 and a system bus 712that couples various system components including the system memory 706,such as read only memory (ROM) 708 and random access memory (RAM) 710,to the processor 702. The system 700 can include a cache of high-speedmemory connected directly with, in close proximity to, or integrated aspart of the processor 702. The system 700 can copy data from the memory706 and/or the storage device 720 to the cache 704 for quick access bythe processor 702. In this way, the cache can provide a performanceboost that avoids processor 702 delays while waiting for data. These andother modules can control or be configured to control the processor 702to perform various actions. Other system memory 706 may be available foruse as well. The memory 706 can include multiple different types ofmemory with different performance characteristics. The processor 702 caninclude any general purpose processor and a hardware module or softwaremodule, such as module 1 (722), module 2 (724), and module 3 (726)stored in storage device 720, configured to control the processor 702 aswell as a special-purpose processor where software instructions areincorporated into the actual processor design. The processor 702 mayessentially be a completely self-contained computing system, containingmultiple cores or processors, a bus, memory controller, cache, etc. Amulti-core processor may be symmetric or asymmetric.

To enable user interaction with the system 700, an input device 714 canrepresent any number of input mechanisms, such as a microphone forspeech, a touch-sensitive screen for gesture or graphical input,keyboard, mouse, motion input, speech and so forth. An output device 716can also be one or more of a number of output mechanisms known to thoseof skill in the art. In some instances, multimodal systems can enable auser to provide multiple types of input to communicate with the system700. The communications interface 718 can generally govern and managethe user input and system output. There is no restriction on operatingon any particular hardware arrangement and therefore the basic featureshere may easily be substituted for improved hardware or firmwarearrangements as they are developed.

Storage device 720 is a non-volatile memory and can be a hard disk orother types of computer readable media which can store data that areaccessible by a computer, such as magnetic cassettes, flash memorycards, solid state memory devices, digital versatile disks, cartridges,random access memories (RAMs) 710, read only memory (ROM) 708, andhybrids thereof.

The storage device 720 can include software modules 722, 724, 726 forcontrolling the processor 702. Other hardware or software modules arecontemplated. The storage device 720 can be connected to the system bus712. In one aspect, a hardware module that performs a particularfunction can include the software component stored in acomputer-readable medium in connection with the necessary hardwarecomponents, such as the processor 702, bus 712, display 716, and soforth, to carry out the function.

FIG. 7B illustrates an example computer system 750 having a chipsetarchitecture that can be used in executing the described method andgenerating and displaying a graphical user interface (GUI). Computersystem 750 is an example of computer hardware, software, and firmwarethat can be used to implement the disclosed technology. System 750 caninclude a processor 752, representative of any number of physicallyand/or logically distinct resources capable of executing software,firmware, and hardware configured to perform identified computations.Processor 752 can communicate with a chipset 754 that can control inputto and output from processor 752. In this example, chipset 754 outputsinformation to output device 756, such as a display, and can read andwrite information to storage device 758, which can include magneticmedia, and solid state media, for example. Chipset 754 can also readdata from and write data to RAM 760. A bridge 762 for interfacing with avariety of user interface components 764 can be provided for interfacingwith chipset 754. Such user interface components 764 can include akeyboard, a microphone, touch detection and processing circuitry, apointing device, such as a mouse, and so on. In general, inputs tosystem 750 can come from any of a variety of sources, machine generatedand/or human generated.

Chipset 754 can also interface with one or more communication interfaces766 that can have different physical interfaces. Such communicationinterfaces can include interfaces for wired and wireless local areanetworks, for broadband wireless networks, as well as personal areanetworks. Some applications of the methods for generating, displaying,and using the GUI disclosed herein can include receiving ordereddatasets over the physical interface or be generated by the machineitself by processor 752 analyzing data stored in storage 758 or 760.Further, the machine can receive inputs from a user via user interfacecomponents 764 and execute appropriate functions, such as browsingfunctions by interpreting these inputs using processor 752.

It can be appreciated that example systems 700 and 750 can have morethan one processor 702 or be part of a group or cluster of computingdevices networked together to provide greater processing capability.

For clarity of explanation, in some instances the present technology maybe presented as including individual functional blocks includingfunctional blocks comprising devices, device components, steps orroutines in a method embodied in software, or combinations of hardwareand software.

In some examples the computer-readable storage devices, mediums, andmemories can include a cable or wireless signal containing a bit streamand the like. However, when mentioned, non-transitory computer-readablestorage media expressly exclude media such as energy, carrier signals,electromagnetic waves, and signals per se.

Methods according to the above-described examples can be implementedusing computer-executable instructions that are stored or otherwiseavailable from computer readable media. Such instructions can comprise,for example, instructions and data which cause or otherwise configure ageneral purpose computer, special purpose computer, or special purposeprocessing device to perform a certain function or group of functions.Portions of computer resources used can be accessible over a network.The computer executable instructions may be, for example, binaries,intermediate format instructions such as assembly language, firmware, orsource code. Examples of computer-readable media that may be used tostore instructions, information used, and/or information created duringmethods according to described examples include magnetic or opticaldisks, flash memory, USB devices provided with non-volatile memory,networked storage devices, and so on.

Devices implementing methods according to these disclosures can comprisehardware, firmware and/or software, and can take any of a variety ofform factors. Typical examples of such form factors include laptops,smart phones, small form factor personal computers, personal digitalassistants, rackmount devices, standalone devices, and so on.Functionality described herein also can be embodied in peripherals oradd-in cards. Such functionality can also be implemented on a circuitboard among different chips or different processes executing in a singledevice, by way of further example.

The instructions, media for conveying such instructions, computingresources for executing them, and other structures for supporting suchcomputing resources are means for providing the functions described inthese disclosures.

Although a variety of examples and other information was used to explainaspects within the scope of the appended claims, no limitation of theclaims should be implied based on particular features or arrangements insuch examples, as one of ordinary skill would be able to use theseexamples to derive a wide variety of implementations. Further andalthough some subject matter may have been described in languagespecific to examples of structural features and/or method steps, it isto be understood that the subject matter defined in the appended claimsis not necessarily limited to these described features or acts. Forexample, such functionality can be distributed differently or performedin components other than those identified herein. Rather, the describedfeatures and steps are disclosed as examples of components of systemsand methods within the scope of the appended claims. Moreover, claimlanguage reciting “at least one of” a set indicates that one member ofthe set or multiple members of the set satisfy the claim.

It should be understood that features or configurations herein withreference to one embodiment or example can be implemented in, orcombined with, other examples or examples herein. That is, terms such as“embodiment”, “variation”, “aspect”, “example”, “configuration”,“implementation”, “case”, and any other terms which may connote anembodiment, as used herein to describe specific features orconfigurations, are not intended to limit any of the associated featuresor configurations to a specific or separate embodiment or examples, andshould not be interpreted to suggest that such features orconfigurations cannot be combined with features or configurationsdescribed with reference to other examples, variations, aspects,examples, configurations, implementations, cases, and so forth. In otherwords, features described herein with reference to a specific example(e.g., embodiment, variation, aspect, configuration, implementation,case, etc.) can be combined with features described with reference toanother example. Precisely, one of ordinary skill in the art willreadily recognize that the various examples or examples describedherein, and their associated features, can be combined with each other.

A phrase such as an “aspect” does not imply that such aspect isessential to the subject technology or that such aspect applies to allconfigurations of the subj ect technology. A disclosure relating to anaspect may apply to all configurations, or one or more configurations. Aphrase such as an aspect may refer to one or more aspects and viceversa. A phrase such as a “configuration” does not imply that suchconfiguration is essential to the subject technology or that suchconfiguration applies to all configurations of the subject technology. Adisclosure relating to a configuration may apply to all configurations,or one or more configurations. A phrase such as a configuration mayrefer to one or more configurations and vice versa. The word “exemplary”is used herein to mean “serving as an example or illustration.” Anyaspect or design described herein as “exemplary” is not necessarily tobe construed as preferred or advantageous over other aspects or designs.Moreover, claim language reciting “at least one of” a set indicates thatone member of the set or multiple members of the set satisfy the claim.

1. A method comprising: receiving, based on at least one attribute of asensor, a sensor identifier configured to uniquely identify the sensor,wherein the sensor identifier is generated based on a hash value of theat least one attribute; and incorporating the sensor identifier inmessages subsequently sent from the sensor.
 2. The method of claim 1,wherein the sensor identifier is a fixed-length hash value based uponvarious lengths of the at least one unique attribute.
 3. The method ofclaim 1, wherein the sensor identifier replaces a previous sensoridentifier.
 4. The method of claim 1, further comprising: prior toreceiving the sensor identifier, determining the sensor is installed ona component in a network; and sending the at least one attribute of thesensor;
 5. The method of claim 1, further comprising: prior to receivingthe sensor identifier, sending a first message comprising the at leastone attribute from the sensor.
 6. The method of claim 5, furthercomprising: sending a second message comprising at least the sensoridentifier; and in response to the second message being received, adetermination is made that the sensor is under an attack.
 7. The methodof claim 6, wherein determining the sensor is under the attack is basedon a match between the sensor identifier and the hash value.
 8. A systemcomprising: a sensor; at least one processor; at least one memorystoring instructions, which when executed by the at least one processor,causes the at least one processor to: receive, based on at least oneattribute of the sensor, a sensor identifier configured to uniquelyidentify the sensor, wherein the sensor identifier is generated based ona hash value of the at least one attribute; and incorporate the sensoridentifier in messages subsequently sent from the sensor.
 9. The systemof claim 8, wherein the sensor identifier is a fixed-length hash valuebased upon various lengths of the at least one unique attribute.
 10. Thesystem of claim 8, wherein the sensor identifier replaces a previoussensor identifier.
 11. The system of claim 8, further comprisinginstructions, which when executed by the at least one processor, causesthe at least one processor to: prior to receiving the sensor identifier,determine the sensor is installed on a component in a network; and sendthe at least one attribute of the sensor;
 12. The system of claim 8,further comprising instructions, which when executed by the at least oneprocessor, causes the at least one processor to: prior to receiving thesensor identifier, send a first message comprising the at least oneattribute from the sensor.
 13. The system of claim 12, instructions,which when executed by the at least one processor, causes the at leastone processor to: send a second message comprising at least the sensoridentifier; and in response to the second message being received, adetermination is made that the sensor is under an attack.
 14. The systemof claim 13, wherein determining the sensor is under the attack is basedon a match between the sensor identifier and the hash value.
 15. Asystem comprising: at least one processor; at least one memory storinginstructions, which when executed by the at least one processor, causesthe at least one processor to: determine a sensor identifier for asensor based on at least one attribute of the sensor, the sensoridentifier configured to uniquely identify the sensor, wherein thesensor identifier is generated based on a hash value of the at least oneattribute; and send the sensor identifier to the sensor.
 16. The systemof claim 15, wherein the sensor identifier is a fixed-length hash valuebased upon various lengths of the at least one unique attribute.
 17. Thesystem of claim 15, further comprising instructions, which when executedby the at least one processor, causes the at least one processor to:prior to determining the sensor identifier, determine the sensor isinstalled on a component in a network; and send the at least oneattribute of the sensor;
 18. The system of claim 15, further comprisinginstructions, which when executed by the at least one processor, causesthe at least one processor to: prior to determining the sensoridentifier, receive a first message comprising the at least oneattribute from the sensor.
 19. The system of claim 18, instructions,which when executed by the at least one processor, causes the at leastone processor to: receive a second message comprising at least thesensor identifier; and in response to the second message being received,determine the sensor is under an attack.
 20. The system of claim 19,wherein determining the sensor is under the attack is based on a matchbetween the sensor identifier and the hash value.